Disruptions in functional network connectivity during alcohol intoxicated driving

Differences in Brain Network Topology Based on Alcohol Use History in Adolescents

Approximately 6 million youth aged 12 to 20 consume alcohol monthly in the United States. The effect of alcohol consumption in adolescence on behavior and cognition is heavily researched; however, little is known about how alcohol consumption in adolescence may alter brain function, leading to long-term developmental detriments. In order to investigate differences in brain connectivity associated with alcohol use in adolescents, brain networks were constructed using resting-state functional magnetic resonance imaging data collected by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) from 698 youth (12-21 years; 117 hazardous drinkers and 581 no/low drinkers). Analyses assessed differences in brain network topology based on alcohol consumption in eight predefined brain networks, as well as in whole-brain connectivity. Within the central executive network (CEN), basal ganglia network (BGN), and sensorimotor network (SMN), no/low drinkers demonstrated stronger and more frequent connections between highly globally efficient nodes, with fewer and weaker connections between highly clustered nodes. Inverse results were observed within the dorsal attention network (DAN), visual network (VN), and frontotemporal network (FTN), with no/low drinkers demonstrating weaker connections between nodes with high efficiency and increased frequency of clustered nodes compared to hazardous drinkers. Cross-sectional results from this study show clear organizational differences between adolescents with no/low or hazardous alcohol use, suggesting that aberrant connectivity in these brain networks is associated with risky drinking behaviors.

Alcohol-induced brain deficit in alcohol dependence

Although numerous adverse effects of alcohol addiction on health, behavior, and brain function were widely reported, the neurobiological mechanism of alcohol dependence remains largely unknown. In this study, a total of twenty-nine patients with alcohol dependence and twenty-nine status-matched normal controls (NCs) were recruited. Percent amplitude of fluctuation (PerAF) was applied to identify alcohol-related brain activity deficits. We found that alcohol dependence was associated with widespread differences in the left orbitofrontal cortex, right higher visual cortex, right supramarginal gyrus, right postcentral gyrus, and bilateral cerebellum posterior lobe with decreased PerAF, but no brain areas with increased PerAF differences were found. ROC curve showed that decreased PerAF revealed extremely high discriminatory power with a high AUC value of 0.953, as well as a high degree of sensitivity (96.6%) and specificity (86.2%), in distinguishing patients with alcohol dependence from NCs. In the alcohol dependence group, the amount of daily alcohol consumption showed significant negative correlations with the right cerebellum posterior lobe and right higher visual cortex. These findings suggest that the cerebellar-visual-orbitofrontal circuit was disturbed by alcohol dependence. The proposed new method of PerAF may be served as a potential biomarker to identify the regional brain activity deficits of alcohol dependence.

Dynamic connectivity patterns of resting-state brain functional networks in healthy individuals after acute alcohol intake

AIMS

Currently, there are only a few studies concerning brain functional alterations after acute alcohol exposure, and the majority of existing studies attach more importance to the spatial properties of brain function without considering the temporal properties. The current study adopted sliding window to investigate the resting-state brain networks in healthy volunteers after acute alcohol intake and to explore the dynamic changes in network connectivity.

MATERIALS AND METHODS

Twenty healthy volunteers were enrolled in this study. Blood-oxygen-level-dependent (BOLD) data prior to drinking were obtained as control, while that 0.5 and 1 h after drinking were obtained as the experimental group. Reoccurring functional connectivity patterns (states) were determined following group independent component analysis (ICA), sliding window analysis and k-means clustering. Between-group comparisons were performed with respect to the functional connectivity states fractional windows, mean dwell time, and the number of transitions.

RESULTS

Three optimal functional connectivity states were identified. The fractional windows and mean dwell time of 0.5 h group and 1 h group increased in state 3, while the fraction window and mean dwell time of 1 h group decreased in state 1. State 1 is characterized by strong inter-network connections between basal ganglia network (BGN) and sensorimotor network (SMN), BGN and cognitive executive network (CEN), and default mode network (DMN) and visual network (VN). However, state 3 is distinguished by relatively weak intra-network connections in SMN, VN, CEN, and DMN. State 3 was thought to be a characteristic connectivity pattern of the drunk brain. State 1 was believed to represent the brain's main connection pattern when awake. Such dynamic changes in brain network connectivity were consistent with participants' subjective feelings after drinking.

CONCLUSION

The current study reveals the dynamic change in resting-state brain functional network connectivity before and after acute alcohol intake. It was discovered that there might be relatively independent characteristic functional network connection patterns under intoxication, and the corresponding patterns characterize the clinical manifestations of volunteers. As a valuable imaging biomarker, dynamic functional network connectivity (dFNC) offers a new approach and basis for further explorations on brain network alterations after alcohol consumption and the alcohol-related mechanisms for neurological damage.

Cannabis and Driving

As more states in the U.S legalize recreational and medicinal cannabis, rates of driving under the influence of this drug are increasing significantly. Aspects of this emerging public health issue potentially pit science against public policy. The authors believe that the legal cart is currently significantly ahead of the scientific horse. Issues such as detection procedures for cannabis-impaired drivers, and use of blood THC levels to gauge impairment, should rely heavily on current scientific knowledge. However, there are many, often unacknowledged research gaps in these and related areas, that need to be addressed in order provide a more coherent basis for public policies. This review focuses especially on those areas. In this article we review in a focused manner, current information linking cannabis to motor vehicle accidents and examine patterns of cannabis-impairment of driving related behaviors, their time courses, relationship to cannabis dose and THC blood levels, and compare cannabis and alcohol-impaired driving patterns directly. This review also delves into questions of alcohol-cannabis combinations and addresses the basis for of per-se limits in cannabis driving convictions. Finally, we distinguish between areas where research has provided clear answers to the above questions, areas that remain unclear, and make recommendations to fill gaps in current knowledge.

Applications of brain imaging methods in driving behaviour research

Applications of neuroimaging methods have substantially contributed to the scientific understanding of human factors during driving by providing a deeper insight into the neuro-cognitive aspects of driver brain. This has been achieved by conducting simulated (and occasionally, field) driving experiments while collecting driver brain signals of various types. Here, this sector of studies is comprehensively reviewed at both macro and micro scales. At the macro scale, bibliometric aspects of these studies are analysed. At the micro scale, different themes of neuroimaging driving behaviour research are identified and the findings within each theme are synthesised. The surveyed literature has reported on applications of four major brain imaging methods. These include Functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), Functional Near-Infrared Spectroscopy (fNIRS) and Magnetoencephalography (MEG), with the first two being the most common methods in this domain. While collecting driver fMRI signal has been particularly instrumental in studying neural correlates of intoxicated driving (e.g. alcohol or cannabis) or distracted driving, the EEG method has been predominantly utilised in relation to the efforts aiming at development of automatic fatigue/drowsiness detection systems, a topic to which the literature on neuro-ergonomics of driving particularly has shown a spike of interest within the last few years. The survey also reveals that topics such as driver brain activity in semi-automated settings or neural activity of drivers with brain injuries or chronic neurological conditions have by contrast been investigated to a very limited extent. Potential topics in driving behaviour research are identified that could benefit from the adoption of neuroimaging methods in future studies. In terms of practicality, while fMRI and MEG experiments have proven rather invasive and technologically challenging for adoption in driving behaviour research, EEG and fNIRS applications have been more diverse. They have even been tested beyond simulated driving settings, in field driving experiments. Advantages and limitations of each of these four neuroimaging methods in the context of driving behaviour experiments are outlined in the paper.

Coupling neuroscience and driving simulation: A systematic review of studies on crash-risk behaviors in young drivers

OBJECTIVE

Motor vehicle crashes are a leading cause of death for adolescents and young adults. The aim of this study is to examine and discuss the state-of-the-art literature which uses neuroscience methods in the context of driving simulation to study adolescent and young adult drivers.

METHODS

We conducted a systematic English-language literature search of Ovid MEDLINE (1946-2020), PsycINFO (1967-2020), PubMed, Web of Science, SCOPUS, and CINAHL using keywords and MeSH terms. Studies were excluded if participants were not within the ages of 15-25, if the driving simulator did not include a visual monitor/computer monitor/projection screen and steering wheel and foot pedals, or brain data (specifically EEG [electroencephalogram], fNIRS [functional near-infrared spectroscopy], or fMRI [functional magnetic resonance imaging]) was not collected at the same time as driving simulation data.

RESULTS

Seventy-six full text articles of the 736 studies that met inclusion criteria were included in the final review. The 76 articles used one of the following neuroscience methods: electrophysiology, functional near-infrared spectroscopy, or functional magnetic resonance imaging. In the identified studies, there were primarily two areas of investigation pursued; driving impairment and distraction in driving. Impairment studies primarily explored the areas of drowsy/fatigued driving or alcohol-impaired driving. Studies of distracted driving primarily focused on cognitive load and auditory and visual distractors.

CONCLUSIONS

Our state of the science systematic review highlights the feasibility for coupling neuroscience with driving simulation to study the neurocorrelates of driving behaviors in the context of young drivers and neuromaturation. Findings show that, to date, most research has focused on examining brain correlates and driving behaviors related to contributing factors for fatal motor vehicle crashes. However, there remains a considerable paucity of research designed to understand underlying brain mechanisms that might otherwise facilitate greater understanding of individual variability of normative and risky driving behavior within the young driving population.

Relapsing-Remitting Multiple Sclerosis Is Associated With Regional Brain Activity Deficits in Motor- and Cognitive-Related Brain Areas

Objective: To identify the abnormal regional spontaneous brain activity associated with relapsing-remitting multiple sclerosis (RRMS) using fractional amplitude of low-frequency fluctuation (fALFF) analysis and their relationships with clinical features.

Methods: A total of 26 RRMS (11 males, 15 females; age, 36.58 ± 10.82 years) and 27 status-matched healthy group (HGs; 12 males, 15 females; age, 35.85 ± 12.05 years) underwent an Expanded Disability Status Scale (EDSS) examination. fALFF was applied to evaluate the abnormal regional brain activity associated with RRMS. Pearson's correlation analysis was applied to calculate the correlations between the signal values of brain areas that exhibited abnormal fALFF values and clinical features. Receiver operating characteristic (ROC) curve was performed to evaluate the sensitivity and specificity of those altered brain areas to distinguish between RRMS and HGs.

Results: Compared with HGs, RRMS exhibited higher fALFF in the right cerebellum posterior lobe, left orbitofrontal cortex, left dorsolateral prefrontal cortex, bilateral supplementary motor area, and right fusiform gyrus and lower fALFF values in the left hippocampus and right precuneus. ROC revealed that these areas showed two good and five fair AUC values (0.77 ± 0.03, 0.729~0.822). However, four combinations with more than five brain regions received the same best discriminatory power with a sensitivity of 96.3% and a specificity of 88.5%. EDSS revealed a negative correlation with supplementary motor area (r = −0.395, p = 0.046).

Conclusions: RRMS is associated with abnormal regional brain activity deficits of motor- and cognitive-related areas. The fALFF parameter may serve as a potential biological marker to discriminate between the two groups.

Ventral Visual Pathway-Cerebellar Circuit Deficits in Alcohol Dependence: Long- and Short-Range Functional Connectivity Density Study

Objective: To identify the underlying intrinsic functional connectome changes in patients with alcohol dependence. Methods: A functional connectivity density (FCD) analysis was used to report on the functional connectivity changes in 24 male patients with alcohol dependence (age, 47.83 ± 6.93 years) and 24 healthy male subjects (age, 47.67 ± 6.99 years). We defined the voxels with a correlated threshold of r > 0.25 inside their neighborhood (radius sphere ≤ 6 mm) as shortFCD, and radius sphere > 6 mm as longFCD. We repeated the network analysis using a range of correlation r thresholds (r = 0.30, 0.35, 0.40, 0.45, 0.50, 0.6, and 0.75) to determine whether between-group differences were substantially affected by the selection of the different R-value thresholds used. A ROC curve was used to test the ability of the FCD in discriminating between the two groups. Pearson's correlation was used to evaluate the relationships between the FCD differences in brain areas and demographic characteristics. Results: The covered differences in brain areas in binarized shortFCD were larger than binarized longFCD in both groups. The intra-group FCD differences did not depend on the selection of different thresholds used. Patients with alcohol dependence were associated with the longFCD deficit in the cerebellum posterior lobe, and shortFCD deficit in the ventral system of the visual pathway and increased shortFCD in the left precentral gyrus, right salience network and right cingulate gyrus. A ROC curve demonstrated that these specific brain areas alone discriminated between the two groups with a high degree of sensitivity and specificity. In the alcohol dependence group, the cerebellum posterior lobe, visual association cortex and the salience network displayed significant correlations with demographic characteristics. Conclusions: The shortFCD analysis was more sensitive than the longFCD analysis in finding differences in the brain areas. The ventral visual pathway-cerebellar circuit deficit appeared to be altered in patients with alcohol dependence.

Aberrant regional brain activities in alcohol dependence: a functional magnetic resonance imaging study

OBJECTIVE

Whether moderate alcohol consumption has health benefits remains controversial, but the harmful effects of excessive alcohol consumption on behavior and brain function are well recognized. The aim of this study was to investigate alcohol-induced regional brain activities and their relationships with behavioral factors.

SUBJECTS AND METHODS

A total of 29 alcohol-dependent subjects (9 females and 20 males) and 29 status-matched healthy controls (11 females and 18 males) were recruited. Severity of alcohol dependence questionnaire (SADQ) and alcohol use disorders identification test (AUDIT) were used to evaluate the severity of alcohol craving. Regional homogeneity (ReHo) analysis was used to explore the alcohol-induced regional brain changes. Receiver operating characteristic (ROC) curve was used to investigate the ability of regional brain activities to distinguish alcohol-dependent subjects from healthy controls. Pearson correlations were used to investigate the relationships between alcohol-induced ReHo differences and behavioral factors.

RESULTS

Alcohol-dependent subjects related to healthy controls showed higher ReHo areas in the right superior frontal gyrus (SFG), bilateral medial frontal gyrus (MFG), left precentral gyrus (PG), bilateral middle temporal gyrus (MTG), and right inferior temporal gyrus (ITG) and lower ReHo areas in the right cerebellum posterior lobe (CPL), left rectal gyrus (RG), and right cluster of pons and cerebellum anterior lobe (CAL). ROC curve revealed high area under the curve (AUC) values (mean ± SD: 0.864 ± 0.028; range: 0.828-0.911) of ReHo differences. Diagnostic analysis showed that these areas alone discriminated alcohol-dependent subjects from healthy controls with high degree of sensitivities (mean ± SD: 81.25% ± 11.49%; range: 62.5%-100%) and specificities (mean ± SD: 81.75% ± 12.36%; range: 67.5%-100%). Years of drink showed negative correlation with left RG (r = -0.493, p = 0.007), the same finding was shown between AUDIT and right CPL (r = -0.52, p = 0.004).

CONCLUSION

Alcohol dependence is associated with aberrant regional activities in multiple brain areas. ReHo analysis may be a useful biological indicator for the detection of regional brain activities in individuals with alcohol dependence.

Aberrant prefrontal-parietal-cerebellar circuits in alcohol dependence

OBJECTIVE

To identify whether the amplitude of low-frequency fluctuations (ALFF) analysis has the potential to serve as a biological marker to detect alcohol-induced spontaneous brain activities and distinguish the patients with alcohol dependence from the healthy subjects.

METHODS

We utilized the ALFF analysis to report on the alcohol-induced spontaneous brain activities in 29 patients with alcohol dependence (9 female, 20 male) relative to 29 status-matched healthy subjects (11 female, 18 male). Receiver operating characteristic curve was used to test the ability of the ALFF analysis in discriminating the patients with alcohol dependence from the healthy subjects. Pearson correlation was used to evaluate the relationships between the signal value of those ALFF differences in brain areas and behavioral characteristics.

RESULTS

Alcohol-induced brain differences located in the right inferior parietal lobule and right supplementary motor area with significant higher ALFF values, and in the left precuneus and bilateral cerebellum posterior lobe with lower ALFF values. The movement-related areas were significantly correlated with each other (P<0.05). Receiver operating characteristic curve revealed good area under the curve values (mean, 0.86±0.079; 0.774-0.951) of the ALFF differences in those specific brain areas, as well as high degree of sensitivities (mean, 80.84%±14.01% or 80%±14.56%; 62.5%-100%) and specificities (mean, 83.32%±9.31%; 70.8%-95.8% or 84.16%±8%; 75%-95.8%).

CONCLUSION

The ALFF analysis may serve as a biological indicator to detect the spontaneous brain activities in patients with alcohol dependence. The prefrontal-parietal-cerebellar circuit appears to be disturbed by long-term alcoholism in patients with alcohol dependence.

Abnormal intrinsic functional hubs in alcohol dependence: evidence from a voxelwise degree centrality analysis

OBJECTIVE

To explore the abnormal intrinsic functional hubs in alcohol dependence using voxelwise degree centrality analysis approach, and their relationships with clinical features.

MATERIALS AND METHODS

Twenty-four male alcohol dependence subjects free of medicine (mean age, 50.21±9.62 years) and 24 age- and education-matched male healthy controls (mean age, 50.29±8.92 years) were recruited. The alcohol use disorders identification test and the severity of alcohol dependence questionnaire (SADQ) were administered to assess the severity of alcohol craving. Voxelwise degree centrality approach was used to assess the abnormal intrinsic functional hubs features in alcohol dependence. Simple linear regression analysis was performed to investigate the relationships between the clinical features and abnormal intrinsic functional hubs.

RESULTS

Compared with healthy controls, alcohol dependence subjects exhibited significantly different degree centrality values in widespread left lateralization brain areas, including higher degree centrality values in the left precentral gyrus (BA 6), right hippocampus (BA 35, 36), and left orbitofrontal cortex (BA 11) and lower degree centrality values in the left cerebellum posterior lobe, bilateral secondary visual network (BA 18), and left precuneus (BA 7, 19). SADQ revealed a negative linear correlation with the degree centrality value in the left precentral gyrus (R²=0.296, P=0.006).

CONCLUSION

The specific abnormal intrinsic functional hubs appear to be disrupted by alcohol intoxication, which implicates at least three principal neural systems: including cerebellar, executive control, and visual cortex, which may further affect the normal motor behavior such as an explicit type of impaired driving behavior. These findings expand our understanding of the functional characteristics of alcohol dependence and may provide a new insight into the understanding of the dysfunction and pathophysiology of alcohol dependence.

Association between motor timing and treatment outcomes in patients with alcohol and/or cocaine use disorder in a rehabilitation program

BACKGROUND

Individuals with Substance Use Disorders (SUDs) have disruptions in the brain's dopaminergic (DA) system and the functioning of its target neural substrates (striatum and prefrontal cortex). These substrates are important for the normal processing of reward, inhibitory control and motivation. Cognitive deficits in attention, impulsivity and working memory have been found in individuals with SUDs and are predictors of poor SUD treatment outcomes and relapse in alcohol and cocaine dependence specifically. Furthermore, the DA system and accompanying neural substrates play a key role in the timing of motor acts (motor timing). Motor timing deficits have been found in DA system related disorders and more recently also in individuals with SUDs. Motor timing is found to correlate with attention, impulsivity and working memory deficits. To our knowledge motor timing, with regards to treatment outcome and relapse, has not been investigated in populations with SUDs.

METHODS/DESIGN

This study aims to investigate motor timing and its relation to treatment response (at 8 weeks) and relapse (at 12 months) in cocaine and/or alcohol dependent individuals. The tested sensitivity values of motor timing parameters will be compared to a battery of neurocognitive tests, owing to the novelty of the motor task battery, the confounding effects of attention and working memory on motor timing paradigms, and high impulsivity levels found in individuals with SUDs.

DISCUSSION

This research will contribute to current knowledge of neuropsychological deficits associated with treatment response in SUDs and possibly provide an opportunity to individualize and modify currently available treatments through the possible prognostic value of motor task performance in cocaine and/or alcohol dependent individuals.

Covert effects of "one drink" of alcohol on brain processes related to car driving: an event-related potential study

The effects of a low dose of alcohol on car driving remain controversial. To address this issue, event-related potentials were recorded while subjects performed a simple car-following task in a driving simulator before and after consuming either "one drink" of beer (representing one standard alcoholic beverage containing 14 g of alcohol) or mineral water (control condition). Subjects who had consumed the determined amount of alcohol demonstrated no detectable outward behavioral signs of intoxication while performing the driving task, an observation in agreement with previous findings. However, the parietal P3 elicited by the brake lights of the preceding car was significantly reduced in amplitude, approximately 50% that observed under the control condition, likely indicating alteration of the neural processing of visual information critical for safe driving. The finding suggests that alcohol begins to affect neural processes for driving even at quantities too low to modify behavior.

Acute effects of alcohol on the human brain: a resting-state FMRI study

The aim of this study is to assess the value of resting-state fMRI in detecting the acute effects of alcohol on healthy human brains. Thirty-two healthy volunteers were studied by conventional MR imaging and resting-state fMRI prior to and 0.5 hours after initiation of acute alcohol administration. The fMRI data, acquired during the resting state, were correlated with different breath alcohol concentrations (BrAC). We use the posterior cingulate cortex/precuneus as a seed for the default mode network (DMN) analysis. ALFF and ReHo were also used to investigate spontaneous neural activity in the resting state. Conventional MR imaging showed no abnormalities on all subjects. Compared with the prior alcohol administration, the ALFF and ReHo also indicated some specific brain regions which are affected by alcohol, including the superior frontal gyrus, cerebellum, hippocampal gyrus, left basal ganglia, and right internal capsule. Functional connectivity of the DMN was affected by alcohol. This resting-state fMRI indicates that brain regions implicated are affected by alcohol and might provide a neural basis for alcohol's effects on behavioral performance.

Neuroimaging of epilepsy: lesions, networks, oscillations

While analysis and interpretation of structural epileptogenic lesion is an essential task for the neuroradiologist in clinical practice, a substantial body of epilepsy research has shown that focal lesions influence brain areas beyond the epileptogenic lesion, across ensembles of functionally and anatomically connected brain areas. In this review article, we aim to provide an overview about altered network compositions in epilepsy, as measured with current advanced neuroimaging techniques to characterize the initiation and spread of epileptic activity in the brain with multimodal noninvasive imaging techniques. We focus on resting-state functional magnetic resonance imaging (MRI) and simultaneous electroencephalography/fMRI, and oppose the findings in idiopathic generalized versus focal epilepsies. These data indicate that circumscribed epileptogenic lesions can have extended effects on many brain systems. Although epileptic seizures may involve various brain areas, seizure activity does not spread diffusely throughout the brain but propagates along specific anatomic pathways that characterize the underlying epilepsy syndrome. Such a functionally oriented approach may help to better understand a range of clinical phenomena such as the type of cognitive impairment, the development of pharmacoresistance, the propagation pathways of seizures, or the success of epilepsy surgery.

Neuronal oscillations and functional interactions between resting state networks

Functional magnetic imaging (fMRI) studies showed that resting state activity in the healthy brain is organized into multiple large-scale networks encompassing distant regions. A key finding of resting state fMRI studies is the anti-correlation typically observed between the dorsal attention network (DAN) and the default mode network (DMN), which - during task performance - are activated and deactivated, respectively. Previous studies have suggested that alcohol administration modulates the balance of activation/deactivation in brain networks, as well as it induces significant changes in oscillatory activity measured by electroencephalography (EEG). However, our knowledge of alcohol-induced changes in band-limited EEG power and their potential link with the functional interactions between DAN and DMN is still very limited. Here we address this issue, examining the neuronal effects of alcohol administration during resting state by using simultaneous EEG-fMRI. Our findings show increased EEG power in the theta frequency band (4-8 Hz) after administration of alcohol compared to placebo, which was prominent over the frontal cortex. More interestingly, increased frontal tonic EEG activity in this band was associated with greater anti-correlation between the DAN and the frontal component of the DMN. Furthermore, EEG theta power and DAN-DMN anti-correlation were relatively greater in subjects who reported a feeling of euphoria after alcohol administration, which may result from a diminished inhibition exerted by the prefrontal cortex. Overall, our findings suggest that slow brain rhythms are responsible for dynamic functional interactions between brain networks. They also confirm the applicability and potential usefulness of EEG-fMRI for central nervous system drug research.

The effects of alcohol on the nonhuman primate brain: a network science approach to neuroimaging

BACKGROUND

Animal studies have long been an important tool for basic research as they offer a degree of control often lacking in clinical studies. Of particular value is the use of nonhuman primates (NHPs) for neuroimaging studies. Currently, studies have been published using functional magnetic resonance imaging (fMRI) to understand the default-mode network in the NHP brain. Network science provides an alternative approach to neuroimaging allowing for evaluation of whole-brain connectivity. In this study, we used network science to build NHP brain networks from fMRI data to understand the basic functional organization of the NHP brain. We also explored how the brain network is affected following an acute ethanol (EtOH) pharmacological challenge.

METHODS

Baseline resting-state fMRI was acquired in an adult male rhesus macaque (n = 1) and a cohort of vervet monkeys (n = 10). A follow-up scan was conducted in the rhesus macaque to assess network variability and to assess the effects of an acute EtOH challenge on the brain network.

RESULTS

The most connected regions in the resting-state networks were similar across species and matched regions identified as the default-mode network in previous NHP fMRI studies. Under an acute EtOH challenge, the functional organization of the brain was significantly impacted.

CONCLUSIONS

Network science offers a great opportunity to understand the brain as a complex system and how pharmacological conditions can affect the system globally. These models are sensitive to changes in the brain and may prove to be a valuable tool in long-term studies on alcohol exposure.

Striatocortical pathway dysfunction in addiction and obesity: differences and similarities

Neuroimaging techniques are starting to reveal significant overlap in the brain circuitry underlying addiction and disorders of dyscontrol over rewarding behaviors (such as binge eating disorder and obesity). Positron emission tomography (PET) has demonstrated impaired striatal dopamine (DA) signaling (decreased D2 receptors) in drug addiction and obesity that is associated with reduced baseline glucose metabolism in medial and ventral prefrontal brain regions. Functional magnetic resonance imaging (fMRI) has documented brain activation abnormalities that also implicate DA-modulated striato-cortical pathways. In this review we map findings from recent neuroimaging studies that differentiate brain activation in drug/food addiction from those in controls within brain networks functionally connected with ventral and dorsal striatum. We show that regions found to be abnormal in addiction and obesity frequently emerge at the overlap of the dorsal and the ventral striatal networks. Medial temporal and superior frontal regions functionally connected with dorsal striatum display greater vulnerability in obesity and eating disorders than in drug addictions, indicating more widespread abnormalities for obesity and eating disorders than for addictions. This corroborates involvement of both ventral striatal (predominantly associated with reward and motivation) and dorsal striatal networks (associated with habits or stimulus response learning) in addiction and obesity but also identify distinct patterns between these two disorders.

Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives

BACKGROUND

Schizophrenia and bipolar disorder share overlapping symptoms and genetic etiology. Functional brain dysconnectivity is seen in both disorders.

METHODS

We compared 70 schizophrenia and 64 psychotic bipolar probands, their respective unaffected first-degree relatives (n = 70, and n = 52), and 118 healthy subjects, all group age-, gender-, and ethnicity-matched. We used functional network connectivity analysis to measure differential connectivity among 16 functional magnetic resonance imaging resting state networks. First, we examined connectivity differences between probands and control subjects. Next, we probed these dysfunctional connections in relatives for potential endophenotypes. Network connectivity was then correlated with Positive and Negative Syndrome Scale (PANSS) scores to reveal clinical relationships.

RESULTS

Three different network pairs were differentially connected in probands (false-discovery rate corrected q < .05) involving five individual resting-state networks: (A) fronto/occipital, (B) anterior default mode/prefrontal, (C) meso/paralimbic, (D) fronto-temporal/paralimbic, and (E) sensory-motor. One abnormal pair was unique to schizophrenia, (C-E), one unique to bipolar, (C-D), and one (A-B) was shared. Two of these three combinations (A-B, C-E) were also abnormal in bipolar relatives but none was normal in schizophrenia relatives (nonsignificant trend for C-E). The paralimbic circuit (C-D), which uniquely distinguished bipolar probands, contained multiple mood-relevant regions. Network relationship C-D correlated significantly with PANSS negative scores in bipolar probands, and A-B with PANSS positive and general scores in schizophrenia.

CONCLUSIONS

Schizophrenia and psychotic bipolar probands share several abnormal resting state network connections, but there are also unique neural network underpinnings between disorders. We identified specific connections that might also be candidate psychosis endophenotypes.

A selective review of simulated driving studies: Combining naturalistic and hybrid paradigms, analysis approaches, and future directions

Naturalistic paradigms such as movie watching or simulated driving that mimic closely real-world complex activities are becoming more widely used in functional magnetic resonance imaging (fMRI) studies both because of their ability to robustly stimulate brain connectivity and the availability of analysis methods which are able to capitalize on connectivity within and among intrinsic brain networks identified both during a task and in resting fMRI data. In this paper we review over a decade of work from our group and others on the use of simulated driving paradigms to study both the healthy brain as well as the effects of acute alcohol administration on functional connectivity during such paradigms. We briefly review our initial work focused on the configuration of the driving simulator and the analysis strategies. We then describe in more detail several recent studies from our group including a hybrid study examining distracted driving and compare resulting data with those from a separate visual oddball task (Fig. 6). The analysis of these data was performed primarily using a combination of group independent component analysis (ICA) and the general linear model (GLM) and in the various studies we highlight novel findings which result from an analysis of either 1) within-network connectivity, 2) inter-network connectivity, also called functional network connectivity, or 3) the degree to which the modulation of the various intrinsic networks were associated with the alcohol administration and the task context. Despite the fact that the behavioral effects of alcohol intoxication are relatively well known, there is still much to discover on how acute alcohol exposure modulates brain function in a selective manner, associated with behavioral alterations. Through the above studies, we have learned more regarding the impact of acute alcohol intoxication on organization of the brain's intrinsic connectivity networks during performance of a complex, real-world cognitive operation. Lessons learned from the above studies have broader applicability to designing ecologically valid, complex, functional MRI cognitive paradigms and incorporating pharmacologic challenges into such studies. Overall, the use of hybrid driving studies is a particularly promising area of neuroscience investigation.

Reactivity of hemodynamic responses and functional connectivity to different states of alpha synchrony: a concurrent EEG-fMRI study

Concurrent EEG-fMRI studies have provided increasing details of the dynamics of intrinsic brain activity during the resting state. Here, we investigate a prominent effect in EEG during relaxed resting, i.e. the increase of the alpha power when the eyes are closed compared to when the eyes are open. This phenomenon is related to changes in thalamo-cortical and cortico-cortical synchronization. In order to investigate possible changes to EEG-fMRI coupling and fMRI functional connectivity during the two states we adopted a data-driven approach that fuses the multimodal data on the basis of parallel ICA decompositions of the fMRI data in the spatial domain and of the EEG data in the spectral domain. The power variation of a posterior alpha component was used as a reference function to deconvolve the hemodynamic responses from occipital, frontal, temporal, and subcortical fMRI components. Additionally, we computed the functional connectivity between these components. The results showed widespread alpha hemodynamic responses and high functional connectivity during eyes-closed (EC) rest, while eyes open (EO) resting abolished many of the hemodynamic responses and markedly decreased functional connectivity. These data suggest that generation of local hemodynamic responses is highly sensitive to state changes that do not involve changes of mental effort or awareness. They also indicate the localized power differences in posterior alpha between EO and EC in resting state data are accompanied by spatially widespread amplitude changes in hemodynamic responses and inter-regional functional connectivity, i.e. low frequency hemodynamic signals display an equivalent of alpha reactivity.